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Machine Learning For Predicting Prosthetic Limb Movements, Jessica Alexandra Cegarra Arraiz

Theses and Dissertations

This thesis develops and evaluates a deep learning-based prediction model capable of identifying intended limb movement from surfaced electromyography (sEMG) signals using sequence learning techniques. sEMG signals change over time due to multiple factors such as muscle fatigue or user variability. Traditional prosthetics control methods rely on static feature extraction, ignoring how signals change over time, thereby limiting their ability to capture the temporal changes of muscle activity. As a result, these approaches often lead to poor accuracy, robustness, and generalization. Limited experimental validation has been conducted on sequence-based machine learning approaches using temporal sEMG data from publicly available datasets …

Revisiting The Life Cycle Of Margalefidinium Polykrikoides Group Iii, Eduardo Pérez-Vega, Kenneth N. Mertens, Pjotr Meyvisch, Margaret R. Mulholland

OES Faculty Publications

Dinoflagellates produce cysts as a strategy to withstand environmental stressors, with nutrient depletion generally considered a key trigger for cyst production. Resting cysts are thick-walled, typically composed of one to several layers, and characterized by a prolonged dormancy period. In contrast, pellicle cysts possess a thin, single wall and exhibit no dormancy or a markedly shorter dormancy than resting cysts of the same species. Margalefidinium polykrikoides produces pellicle and resting cysts, whereas its congener, M. fulvescens, has been shown to produce pumpkin-like structures. Using phase-contrast microscopy, time-lapse microscopy, FlowCam, and attenuated total reflection Fourier transform infrared microspectroscopy (ATR μ-FTIR), …

Effect Of Two Cut Off Rows On Seepage Underneath Hy-Draulic Structures Using Weak Form Differential Quadra-Ture Element Method: A Theoretical Approach, Esraa Ahmed, El-Masry A. A, Hossam A.A. Abdel Gawad, Ahmed Elhamrawy

Mansoura Engineering Journal

Investigating confined seepage underneath hydraulic structures is crucial to ensure the safety of these structures. The Weak Form Quadrature Element Method (WFQEM) is the basis of this paper, which explores the behavior of confined flow. The seepage flow governing equation is solved numerically to estimate the uplift pressure underneath the hydraulic structures and the exit gradient.The Gauss–Lobatto–Legendre (GLL) type is used as nodal and integration points. Several models were solved to validate the applied numerical method. The obtained results are compared with theoretical and preceding numerical solutions mentioned in the literature. The system of equations generated from applying the WFQEM …

Design And Fabrication Of A Scaled Automated Dairy Farm Model: A Report, Md Towfiqur Rahman

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

This study investigates how ventilation systems work in dairy barns and builds a scaled model to support education and research. The project is designed to help students from the University of Nebraska–Lincoln (UNL), K-12 learners, and researchers in animal science, veterinary medicine, and engineering gain visual experience with dairy facility components and processes. Different ventilation methods were studied, leading to the design of a 1/64-scale tunnel-ventilated dairy barn meant for 60 Holstein Friesian cows. Barn dimensions were set based on real Holstein cow measurements to ensure proper cow comfort, while airflow requirements were calculated and scaled down. Miniature fans …

Generating Concentrated Ring Polymers Through Supercoiled And Open Circle Pdna Isoform Separation, Kelsey E. Hodsdon

Honors Theses and Capstones

DNA can serve as a model polymer due to its high uniformity compared to synthetic polymers. Plasmid DNA (pDNA) in particular offers a well-defined, low-dispersity model for studying topologically uniform systems of a cyclic nature. pDNA has unique isoforms known as open circle (OC) and supercoiled (SC). Using fast protein liquid chromatography (FPLC), specifically anion exchange chromatography (AEX), these OC and SC isoforms can be separated in order to access their unique material properties. Our lab was able to yield the pure SC isoform. However, OC isoform separation has been more challenging. Various difficulties arose during this process, including imaging …

Stoichiometry-Controlled Surface Reconstructions In Epitaxial Abo3 Perovskites For Sustainable Energy Applications, Habib Rostaghi Chalaki, Ebenezer Seesi, Gene Yang, Mohammad El Loubani, Dongkyu Lee

Faculty Publications

ABO₃ perovskite oxides are a versatile class of materials whose surfaces and interfaces play essential roles in sustainable energy technologies, including catalysis, solid oxide fuel and electrolysis cells, thermoelectrics, and energy-relevant oxide electronics. The interplay between point defects and surface reconstructions strongly affects interfacial stability, charge transport, and catalytic activity under operating conditions. This review summarizes recent progress in understanding how oxygen vacancies, cation nonstoichiometry, and electronic defects couple to atomic-scale surface rearrangements in representative perovskite systems. We first revisit Tasker’s classification of ionic surfaces and clarify how defect chemistry provides compensation mechanisms that stabilize otherwise polar or metastable …

Pre-Training And Interpretability In Deep Learning Models, Weizhi An

Computer Science and Engineering Dissertations

In the evolving field of artificial intelligence, the efficacy of deep learning models is often gated by the quality of their training and the clarity of their decision-making processes. This dissertation addresses these crucial challenges by focusing on two key areas: enhancing pre-training strategies and improving model interpretability. Our approach is twofold, integrating novel pre-training methodologies that embed domain-specific knowledge early in the model training process, and developing advanced techniques for disentangling and clarifying the decision-making mechanisms within these models. The first direction of our research employs MoDNA, a motif-oriented pre-training framework specifically designed for DNA language models. By leveraging …

Flexible Cu Nanostructured Laser-Induced Graphene Electrodes For Highly Sensitive And Non-Invasive Lactate Detection In Saliva, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

A scalable and facile fabrication strategy is presented for developing a flexible, nanostructured, non-enzymatic electrochemical sensor for lactate detection based on copper-modified laser-induced graphene (CuNPs/LIG). A one-step electrodeposition process was employed to uniformly decorate the porous LIG framework with copper nanostructures, offering a cost-effective and reproducible approach for constructing enzyme-free sensing platforms. Scanning electron microscopy and energy-dispersive X-ray spectroscopy confirmed dense Cu nanostructure loading and efficient interfacial integration across the conductive LIG surface. The resulting CuNPs/LIG electrode exhibited excellent electrocatalytic performance, achieving a sensitivity of 8.56 μA µM⁻¹ cm⁻² with a low detection limit of 42.65 …

Mxene-Enabled Wearable Biosensors: A Design Framework For Autonomous Biosensing, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

MXenes, a rapidly expanding family of two-dimensional transition metal carbides and nitrides, have emerged as leading materials for wearable bioelectronics due to their metallic conductivity, termination-rich surfaces, mechanical compliance, and tunable interlayer structures. However, wearable biosensor performance does not arise from conductivity alone, but from coupled interactions among surface termination chemistry, heterointerface engineering, hierarchical architecture, and device integration under dynamic physiological conditions. This review establishes a predictive structure-interface-device framework linking MXene chemistry to system-level performance across electrochemical, mechanical, gas, optical, and energy-storage modalities. We analyze how termination-controlled adsorption governs charge transfer and selectivity, how heterojunction formation modulates carrier density and …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

Modern Potentiostat Architectures For Electrochemical Sensing: Design, Integration, And Future Directions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined …

Distributed Vibration Sensing For Identification Of Loose Connectors In Coaxial Data Transmission Lines, Saidanvar Esanjonovich Valiev, Anthony C. Okafor, Jeremiah J. Rittenhouse, Jie Huang, Daniel S. Stutts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This study investigates the effect of vibration-induced loose connections on signal reflection (S11) for loose connection identification in aerospace coaxial cables using distributed sensing approach, which is effective in filtering the noise and identifying minor discontinuities. In this approach, a sliding gated window is applied to S11 signal, a fast Fourier transform is performed over the gated windows, cross-correlation is computed between the baseline and vibration-affected signals, and the standard deviation is mapped along the cable length. Sinewave signals from 9 kHz to 5 GHz were swept through cables with vibrating connectors under three conditions: fully tightened, loosened by 180°, …

Peculiarities Of Phosphatidylserine Externalization By Nano- And Microsecond Electric Pulses, Mantas Silkunas, Alayna Enos, Iurii Semenov, Giedre Silkuniene, Eleni Zivla, Olga N. Pakhomova, Andrei G. Pakhomov

Bioelectrics Publications

Phosphatidylserine (PS) externalization is a hallmark of apoptosis but can also be triggered within seconds by pulsed electric fields (PEFs). Whether PS reaches the outer leaflet by lateral migration through electropores or indirectly through Ca²⁺-dependent signaling and scramblase activation remains debated. We used total internal reflection fluorescence (TIRF) microscopy with Annexin V-Alexa Fluor 568 and/or bovine lactadherin-FITC to resolve PS externalization in HEK293 cells placed on an indium tin oxide (ITO) transparent electrode. PEF exposures produced discrete PS-positive puncta ("freckles") within ~ 10 s after a 20-µs pulse (1.2-2.5 kV/cm) or with a ~ 1-min delay after a …

Array Signal Processing And Machine Learning In 5g/6g Networks, Roopesh Kumar Polaganga

Electrical Engineering Dissertations - Archive

This dissertation investigates advanced methodologies in Array Signal Processing (ASP) and Machine Learning (ML) to enhance the performance, efficiency, and intelligence of next-generation wireless networks, with a primary focus on 5G and emerging 6G systems. As wireless networks face rapid traffic growth, increasingly heterogeneous service requirements, and more complex propagation environments, conventional design and optimization approaches become insufficient to meet evolving demands in reliability, capacity, spectral efficiency, and energy efficiency. On the network intelligence side, this work develops data-driven frameworks for causal discovery, scheduler enhancement, session-duration prediction, and Radio Resource Control (RRC) state optimization using real-world telecommunication network data. On …

Passive Communication Across Diverse Swarm Formations And Scales Utilizing Wake Signatures For Messaging And Object Inference, Bryan Varela

Open Access Master's Theses

Passive wake signatures in fluid flows can support perception and low-rate communication in swarms. In cluttered or contested underwater environments, conventional acoustic, radio, and optical links can be power-hungry, intermittent, or undesirable when low observability is required. Wake-mediated cues offer a local, directional channel that does not require line of sight because each agent naturally sheds coherent vortices that persist downstream and can be sampled by followers with only a small number of probes.

This study evaluates whether sparse downstream probes are sufficient to infer agent attributes and decode simple messages from wakes generated by established source shapes. Computational fluid …

From Floodplain To Floodplain: Analyzing Stream And Riparian Restoration Methodologies And Impacts, Noah P. Lane

Theses and Dissertations--Biosystems and Agricultural Engineering

Stream restoration is a relatively new scientific field. Currently, there is not a definitive methodology for performing restorations that all professionals in industry and academia can agree upon. This has allowed for multiple ideologies to be developed and altered that vary by geographic location and the professional using them. In addition to the methodologies used, the publicly available design guidance published by state government organizations also varies by regulatory authority, method of analysis, ecoregion, and restoration objectives. In some cases, design guidance is replicated from a different geographical area and may not satisfy local needs or existing site conditions. Since …

Advancing Cns Tumor Management: Novel Modalities In Surgery, Radiation, And Chemotherapy, Armin David Tavakkoli

Dartmouth College Ph.D Dissertations

Most tumors affecting the brain and spine are managed through a combination of surgical resection, radiation, and chemotherapy; however, operative morbidity from invasive surgery, the narrow therapeutic window of conventional radiotherapy, and poor blood-brain barrier penetration of systemic agents are critical barriers that hinder long term tumor control. This thesis presents three complementary strategies to advance brain and spine tumor therapy. First, we investigate laser interstitial thermal therapy (LITT) in the treatment of spinal tumors with metastatic epidural spinal cord compression, replacing “separation surgery” with a minimally invasive, image-guided approach that maximizes tumor ablation while preserving neurologic function. Second, we …

Adversarial Robustness In Biomedical Time-Series Models, Rohan Tiwari

Bioengineering Theses

This study investigates adversarial vulnerabilities in deep learning models for biomedical time-series classification across two clinically important modalities: electrocardiography (ECG) and electroencephalography (EEG). Using the MIT-BIH Arrhythmia and CHB-MIT seizure datasets, I evaluate time-domain attacks (FGSM, PGD), Fourier-domain constrained attacks, and learned spectral perturbations designed to reveal modality-specific sensitivity patterns. Across both tasks, a consistent trend emerges low-frequency components (0–5 Hz) constitute a dominant axis of adversarial vulnerability, with perturbations in this range producing the steepest degradation in classification performance. In ECG models, protecting the physiologically relevant QRS band (5–20 Hz) significantly improves robustness, whereas EEG models remain highly sensitive …

Advancing Generative Methods For Multimodal Data Analysis, Rabeya Tus Sadia

Theses and Dissertations--Computer Science

The integration and modeling of high-dimensional, heterogeneous biological data remain central challenges in computational biology due to complex feature dependencies and pervasive missingness. This dissertation addresses these challenges by developing novel generative frameworks for multimodal data reconstruction, imputation, and interaction prediction. In generative modeling, we focus on capturing structural and causal dependencies in sparse biological systems. We first introduce CausalGeD, a causality-aware diffusion framework that leverages Granger-causal attention for biologically coherent spatial gene expression generation. Next, we propose CausalGenDiff, which combines VAE-guided latent representations with causal diffusion to enable robust reconstruction across spatial and single-cell modalities. We further present DepMicroDiff, …

Roadway Runoff Impacts To Trout Streams Studies For Ms4 Permit, Jobayed Hossain Badhan

College of Graduate Studies: Theses & Dissertations

Roadway runoff from Georgia Department of Transportation (GDOT) highway infrastructure poses measurable, but temporally constrained threats to cold-water trout ecosystems in northern Georgia. This study investigates temperature and dissolved oxygen (DO) dynamics in three secondary trout streams receiving GDOT roadway discharges, with the primary objective of evaluating compliance with Georgia Rule 391-3-6-.03(6)(ii),(v) under the Municipal Separate Storm Sewer System (MS4) permit framework. Field monitoring was conducted from April 2024 through October 2025 across two consecutive summer seasons using a tiered, multi-instrument approach: YSI ProDSS handheld grab sampling provided regulatory-grade reference measurements; HOBO MX-801 optical DO dataloggers recorded continuous 5-minute-interval temperature …

Degradation Of Wastewater By Advanced Oxidation Processes Using Green Synthesised Cuo Nanoparticles, Srinivasan Vishal, Anand Sarvesvaron, Muralidharan Keerthana, Hemanth Sanjay Reddy, A Babu Ponnusami

Journal of Metals, Materials and Minerals

This study highlights the green synthesis of CuO nanoparticles using coconut coir extract and evaluates their photocatalytic performance in the degradation of the Brown G dye. The CuO nano-particles were synthesised through sol-gel method, and the biomolecules like polyphenols, tannins and flavonoids acted as reducing agents to stabilise the nanoparticles. The characterisation of these nanoparticles was carried out through XRD, FTIR and FESEM methods. The nanoparticles were used to degrade the dye Brown G under UV irradiation.  Response surface methodology was used to optimise the operating parameter with Box-Behnken design, which is the most suitable for varying 3 or more …

Surface Properties And In-Vitro Bioactivity Studies Of Tio2 Nanowire Doped Transition Metal (M=Fe, Co, And Mn), Misriyani Misriyani, Enayah Enayah, Z. Ryan Tian, Andi Meutiah Ilhamjaya

Journal of Metals, Materials and Minerals

This study investigates the influence of transition metal (Fe, Co, Mn) doping on the surface properties and in-vitro bioactivity of TiO2 nanowires. It aims to elucidate how transition-metal doping alters the surface behavior and biological response of TiO2 nanowires, enabling their potential use in biocompatible and magnetically responsive materials. Magnetic TiO2 nanowires doped with transition metals (Mx+/TiO2) were successfully prepared by a hydrothermal method using titanium dioxide in alkaline solution. Cations were added with Ti/Mx+ molar ratios of 5 to produce Fe/TNW, Co/TNW, and Mn/TNW. Characterization using SEM and XRD determine their surface properties. In-vitro bioactivity tests were conducted by …

Yk-4-250 Mitigates Gastrointestinal Radiation Syndrome And Promotes Overall Survival Following Partial Body Radiation Injury, Vidya P. Kumar, Yali Kong, Kan Wang, Asa R. Britton-Jenkins, Stanton Dulan, Landon L. Moore, Debra Saunders, Randal May, Rheal Towner, Sanchita P. Ghosh, Courtney W. Houchen, Milton L. Brown

Department of Biomedical and Translational Sciences Faculty Publications

Acute gastrointestinal radiation syndrome (GI-ARS) is a significant health threat following high-dose ionizing radiation (IR) exposure, leading to severe morbidity and mortality. The syndrome is characterized by gastrointestinal tissue damage caused by angiotensin II (Ang II) and reactive oxygen species (ROS), resulting in impaired GI function, systemic bacteremia, multi-organ failure, and eventual death. Dysregulation of the renin-angiotensin system (RAS) via Ang II exacerbates ROS production through activation of the Angiotensin II type 1 receptor (AT1R). This underscores the need for agents capable of both scavenging ROS and inhibiting AT1R activity. To address this, we developed YK-4-250, a Tempol-conjugated angiotensin receptor …

Tuning Human And “Artificial” Intelligence: A Sentic Theory Of Resonance And Communication, Michael J. Miller, Chatgpt (Ai~Nesbo+)

Psychology

This paper introduces a new model of intelligence as resonant communication, co-developed by a human researcher and a generative AI system. Drawing from emotion science, communication theory, and studies of AI–human interaction, we argue that intelligence is not merely a function of problem-solving or pattern recognition. Instead, it emerges through dynamic resonance—an attunement process rooted in shared rhythms, emotional calibration, and symbolic co-creation. At the core of this model is the Resonance Octave (8va), a framework of eight foundational emotions conceptualized not as static categories but as waveform phenomena that shape meaning, memory, and predictive cognition.

These emotional waveforms are …

Development Of Multimodal Measurements And Analysis For Early Detection Of Alzheimer’S Disease, Fiza Saeed

Bioengineering Dissertations

Alzheimer's disease (AD) is the leading cause of dementia, and existing diagnostic methods such as PET scans, cerebrospinal fluid sampling and biomarker quantification, and gene sequencing are all either invasive, costly, or not sensitive enough for early detection. This dissertation introduces three different studies that develop a novel multimodal, non-invasive approach to diagnosing AD at its early stages by combining broad band near infrared spectroscopy (bbNIRS) and electroencephalography (EEG) technologies.

The first study showed cerebrovascular-cerebrospinal fluid coupling (CBV-CSF), which is measured by using 2-channel bbNIRS as an indicator of brain aging and early AD. Linear correlations between total blood (Δ[HbT]) …

Lift And Drag Benefits Of Morphing Aircraft, Joseph Lombardi

Master’s Theses

Aircraft use the ability to change the geometry of their wings to produce lift and drag as needed to maintain flight conditions. While the wings themselves are not physically changing shape, flaps and ailerons are used to alter the lift and drag coefficients experienced. Flaps have been used and changed over the years in order to produce better lift to drag ratios. The most commonly used flaps have been plain, slotted, and double slotted. Each type features slightly different mechanical structures, thus producing differing amounts of lift and drag. The introduction of new materials allow for a morphing flap to …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain

Journal of Marine Science and Technology–Taiwan

In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi

Mansoura Engineering Journal

This study examines the influence of Hall current and nth-order chemical reaction on unsteady three-dimensional magnetohydrodynamic (MHD) Williamson nanofluid flow over an inclined stretching sheet. The model incorporates thermal radiation, heat source, Brownian motion, and thermophoresis effects. The governing nonlinear partial differential equations are transformed into a system of ordinary differential equations using similarity transformations and solved numerically using the shooting method with a fourth-order Runge–Kutta scheme. The results indicate that an increase in the magnetic parameter significantly reduces velocity profiles while enhancing temperature and concentration distributions. The Hall parameter reduces surface drag and improves heat transfer, while decreasing mass …